// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#include <stdio.h>
#include <string.h>
#include <sys/ipc.h>
#include <sys/msg.h>
#include <sys/types.h>
#include "paddle/extension.h"

#define MAX_BSZ 256
#define MAX_DRAFT_TOKENS 6

struct msgdata {
  int64_t mtype;
  int mtext[MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ +
            2];  // stop_flag, bsz, accept_num*bsz, tokens...
};

void SpeculateGetOutput(const paddle::Tensor& x,
                        int64_t rank_id,
                        bool wait_flag,
                        int msg_queue_id,
                        bool get_each_rank) {
  if (!get_each_rank && rank_id > 0) {
    return;
  }

  if (const char* inference_msg_queue_id_env_p =
          std::getenv("INFERENCE_MSG_QUEUE_ID")) {
    std::string inference_msg_queue_id_env_str(inference_msg_queue_id_env_p);
    int inference_msg_queue_id_from_env =
        std::stoi(inference_msg_queue_id_env_str);
#ifdef GET_OUTPUT_DEBUG
    std::cout << "Your INFERENCE_MSG_QUEUE_ID is: "
              << inference_msg_queue_id_from_env << std::endl;
#endif
    msg_queue_id = inference_msg_queue_id_from_env;
  }

  static struct msgdata msg_rcv;

  static key_t key = ftok("./", msg_queue_id);

  static int msgid = msgget(key, IPC_CREAT | 0666);

  int64_t* out_data = const_cast<int64_t*>(x.data<int64_t>());
  int ret = -1;
  if (!wait_flag) {
    ret = msgrcv(msgid,
                 &msg_rcv,
                 (MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ + 2) * 4,
                 0,
                 IPC_NOWAIT);
  } else {
    ret = msgrcv(
        msgid, &msg_rcv, (MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ + 2) * 4, 0, 0);
  }
  if (ret == -1) {
    out_data[0] = -2;
    out_data[1] = 0;
    return;
  }
  int bsz = msg_rcv.mtext[1];

  for (int64_t i = 0; i < MAX_BSZ * MAX_DRAFT_TOKENS + MAX_BSZ + 2; i++) {
    out_data[i] = (int64_t)msg_rcv.mtext[i];
  }
  return;
}

void SpeculateGetOutputStatic(const paddle::Tensor& x,
                              int64_t rank_id,
                              bool wait_flag,
                              bool get_each_rank) {
  SpeculateGetOutput(x, rank_id, wait_flag, 1, get_each_rank);
}

void SpeculateGetOutputDynamic(const paddle::Tensor& x,
                               int64_t rank_id,
                               bool wait_flag,
                               int msg_queue_id,
                               bool get_each_rank) {
  SpeculateGetOutput(x, rank_id, wait_flag, msg_queue_id, get_each_rank);
}

PD_BUILD_OP(speculate_get_output)
    .Inputs({"x"})
    .Attrs({"rank_id: int64_t", "wait_flag: bool", "get_each_rank: bool"})
    .Outputs({"x_out"})
    .SetInplaceMap({{"x", "x_out"}})
    .SetKernelFn(PD_KERNEL(SpeculateGetOutputStatic));

PD_BUILD_OP(speculate_get_output_dynamic)
    .Inputs({"x"})
    .Attrs({"rank_id: int64_t",
            "wait_flag: bool",
            "msg_queue_id: int",
            "get_each_rank: bool"})
    .Outputs({"x_out"})
    .SetInplaceMap({{"x", "x_out"}})
    .SetKernelFn(PD_KERNEL(SpeculateGetOutputDynamic));
